Geophysical inversion and modeling beyond the standard
2024-03-19
pyGIMLi objects (Mesh, DataContainer, matrix types, etc.), geostatistical vs. smoothness regularization, treatment of subsurface regions, adding prior data.LSQRinversion framework enabling parameter constraints (from Wagner et al. 2019)MultiFrameModelling framework for temporally/spectrally/spatially constrained inversionTimelapseERT class with different strategies, e.g. 4D inversion“In open source, we feel strongly that to really do something well, you have to get a lot of people involved.”
– Linus Torvalds
#pyGIMLi chat on Mattermost!SEGwebinar repository.pg environment with the required dependencies (in particular pygimli=1.5.0).Follow without a local installation
You can also visit https://colab.research.google.com, open an empty notebook and type !pip install pygimli.